{
 "cells": [
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>SP500</th>\n",
       "      <th>USDRMB</th>\n",
       "      <th>SHINDEX</th>\n",
       "      <th>SZINDEX</th>\n",
       "      <th>USDINDEX</th>\n",
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       "      <th>0</th>\n",
       "      <td>2000-01-03 00:00:00</td>\n",
       "      <td>1455.22</td>\n",
       "      <td>8.2795</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>1.0273</td>\n",
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       "      <th>1</th>\n",
       "      <td>2000-01-04 00:00:00</td>\n",
       "      <td>1399.42</td>\n",
       "      <td>8.2798</td>\n",
       "      <td>1406.371</td>\n",
       "      <td>3497.060</td>\n",
       "      <td>114.3583</td>\n",
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       "      <th>2</th>\n",
       "      <td>2000-01-05 00:00:00</td>\n",
       "      <td>1402.11</td>\n",
       "      <td>8.2799</td>\n",
       "      <td>1409.682</td>\n",
       "      <td>3486.285</td>\n",
       "      <td>114.6221</td>\n",
       "      <td>1.0316</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-06 00:00:00</td>\n",
       "      <td>1403.45</td>\n",
       "      <td>8.2798</td>\n",
       "      <td>1463.942</td>\n",
       "      <td>3655.199</td>\n",
       "      <td>115.1688</td>\n",
       "      <td>1.0295</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-07 00:00:00</td>\n",
       "      <td>1441.47</td>\n",
       "      <td>8.2797</td>\n",
       "      <td>1516.604</td>\n",
       "      <td>3828.040</td>\n",
       "      <td>114.9098</td>\n",
       "      <td>1.0280</td>\n",
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      ],
      "text/plain": [
       "                  Date    SP500  USDRMB   SHINDEX   SZINDEX  USDINDEX  EURUSD\n",
       "0  2000-01-03 00:00:00  1455.22  8.2795       NaN       NaN  114.4743  1.0273\n",
       "1  2000-01-04 00:00:00  1399.42  8.2798  1406.371  3497.060  114.3583  1.0295\n",
       "2  2000-01-05 00:00:00  1402.11  8.2799  1409.682  3486.285  114.6221  1.0316\n",
       "3  2000-01-06 00:00:00  1403.45  8.2798  1463.942  3655.199  115.1688  1.0295\n",
       "4  2000-01-07 00:00:00  1441.47  8.2797  1516.604  3828.040  114.9098  1.0280"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats as ss\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "df = pd.read_excel(\"yyf_prices.xls\")\n",
    "df[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.index=df.pop('Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SP500</th>\n",
       "      <th>USDRMB</th>\n",
       "      <th>SHINDEX</th>\n",
       "      <th>SZINDEX</th>\n",
       "      <th>USDINDEX</th>\n",
       "      <th>EURUSD</th>\n",
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       "    <tr>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-03 00:00:00</th>\n",
       "      <td>1455.22</td>\n",
       "      <td>8.2795</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>114.4743</td>\n",
       "      <td>1.0273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04 00:00:00</th>\n",
       "      <td>1399.42</td>\n",
       "      <td>8.2798</td>\n",
       "      <td>1406.371</td>\n",
       "      <td>3497.060</td>\n",
       "      <td>114.3583</td>\n",
       "      <td>1.0295</td>\n",
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       "    <tr>\n",
       "      <th>2000-01-05 00:00:00</th>\n",
       "      <td>1402.11</td>\n",
       "      <td>8.2799</td>\n",
       "      <td>1409.682</td>\n",
       "      <td>3486.285</td>\n",
       "      <td>114.6221</td>\n",
       "      <td>1.0316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06 00:00:00</th>\n",
       "      <td>1403.45</td>\n",
       "      <td>8.2798</td>\n",
       "      <td>1463.942</td>\n",
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       "      <td>115.1688</td>\n",
       "      <td>1.0295</td>\n",
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       "    <tr>\n",
       "      <th>2000-01-07 00:00:00</th>\n",
       "      <td>1441.47</td>\n",
       "      <td>8.2797</td>\n",
       "      <td>1516.604</td>\n",
       "      <td>3828.040</td>\n",
       "      <td>114.9098</td>\n",
       "      <td>1.0280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       SP500  USDRMB   SHINDEX   SZINDEX  USDINDEX  EURUSD\n",
       "Date                                                                      \n",
       "2000-01-03 00:00:00  1455.22  8.2795       NaN       NaN  114.4743  1.0273\n",
       "2000-01-04 00:00:00  1399.42  8.2798  1406.371  3497.060  114.3583  1.0295\n",
       "2000-01-05 00:00:00  1402.11  8.2799  1409.682  3486.285  114.6221  1.0316\n",
       "2000-01-06 00:00:00  1403.45  8.2798  1463.942  3655.199  115.1688  1.0295\n",
       "2000-01-07 00:00:00  1441.47  8.2797  1516.604  3828.040  114.9098  1.0280"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dfrets = 100* df.pct_change().dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SP500</th>\n",
       "      <th>USDRMB</th>\n",
       "      <th>SHINDEX</th>\n",
       "      <th>SZINDEX</th>\n",
       "      <th>USDINDEX</th>\n",
       "      <th>EURUSD</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-05 00:00:00</th>\n",
       "      <td>0.192222</td>\n",
       "      <td>0.001208</td>\n",
       "      <td>0.235429</td>\n",
       "      <td>-0.308116</td>\n",
       "      <td>0.230678</td>\n",
       "      <td>0.203983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06 00:00:00</th>\n",
       "      <td>0.095570</td>\n",
       "      <td>-0.001208</td>\n",
       "      <td>3.849095</td>\n",
       "      <td>4.845100</td>\n",
       "      <td>0.476959</td>\n",
       "      <td>-0.203567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07 00:00:00</th>\n",
       "      <td>2.709038</td>\n",
       "      <td>-0.001208</td>\n",
       "      <td>3.597274</td>\n",
       "      <td>4.728634</td>\n",
       "      <td>-0.224887</td>\n",
       "      <td>-0.145702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-10 00:00:00</th>\n",
       "      <td>1.118997</td>\n",
       "      <td>-0.003623</td>\n",
       "      <td>1.879726</td>\n",
       "      <td>2.441040</td>\n",
       "      <td>0.061004</td>\n",
       "      <td>-0.262646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-11 00:00:00</th>\n",
       "      <td>-1.306257</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-4.228237</td>\n",
       "      <td>-5.219963</td>\n",
       "      <td>0.086276</td>\n",
       "      <td>0.692480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        SP500    USDRMB   SHINDEX   SZINDEX  USDINDEX  \\\n",
       "Date                                                                    \n",
       "2000-01-05 00:00:00  0.192222  0.001208  0.235429 -0.308116  0.230678   \n",
       "2000-01-06 00:00:00  0.095570 -0.001208  3.849095  4.845100  0.476959   \n",
       "2000-01-07 00:00:00  2.709038 -0.001208  3.597274  4.728634 -0.224887   \n",
       "2000-01-10 00:00:00  1.118997 -0.003623  1.879726  2.441040  0.061004   \n",
       "2000-01-11 00:00:00 -1.306257  0.000000 -4.228237 -5.219963  0.086276   \n",
       "\n",
       "                       EURUSD  \n",
       "Date                           \n",
       "2000-01-05 00:00:00  0.203983  \n",
       "2000-01-06 00:00:00 -0.203567  \n",
       "2000-01-07 00:00:00 -0.145702  \n",
       "2000-01-10 00:00:00 -0.262646  \n",
       "2000-01-11 00:00:00  0.692480  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfrets.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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cyP077wfg2S7Pmscv27/M68+l4ngF+8v2s3BhTUtc3i7P4xrz89xR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\nCIIgCEGOGHSCIAiCIAhBzv8Dzw6WBFKyi18AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd57e92198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['SP500','SHINDEX','SZINDEX']].plot(grid='on',figsize=(10,6),title='Stock Prices');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gOMI+fLdnDYTHQssBduiU2hHRCHJ22493LLZvyz+ouFzL0+DiV+u2tnpGgU5E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\nTgWdiIiISMKpoBMRERFJuH8CZnfPzEuLNwkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd641b0cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['EURUSD','USDRMB']].plot(grid='on',figsize=(10,6),title='FX');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fd53ad13c8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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asrKyiLW45XN+psl++we9cCe/8RzHDbmNzevXMvz8Ezjn4VHUarAbk994nlnj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\ng9mzhtzG4AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd53947710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.subplot(2,1,1)\n",
    "dfrets.SP500.plot(grid='on',color = '#7F3620',title='SP500 Returns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fd5e52f390>"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6NMTwSjX03ZobZ4CXIGhZD0DYtpXizkcrEaKIiEhNs+TE3o3xpt5tJalT/x4z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\nIgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd5e55bcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.subplot(2,1,2)\n",
    "\n",
    "df.USDRMB[2500:].plot(grid='on',color = '#F2B33D',title='人民币USD vs RMB FX',figsize=(12,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fd5ead6400>"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KpVkTXKugcQUwasJbQBPaftgxWbNcG7pOOR39l13jmo2oz1pbSDVEwk6hNlxA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\nCPG+9nehr0zSaUPjajeGKK3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AOLx7o/2U5bwPb8xSyXfONHjb3aMhIPTrtHA4BVKyP6pN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\n413H6f6LZuZ4ezbqKChNt6W/zDet1o47mGUWsr4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4nT75y5gDzHvFcJxhMeGxtNno7HvQ\nb4l3l4ddOy/WwY6d9jhwJxqj5R332U/nny7ClKaoPYgB7C92JaO69ilSSvT99SKnk7lfixE4LAOa\naGjA0HMvIf7wE4iaJsNGHnbanKDiZVYRt1jOhW+u7O9Xh4YLT3CE8LVP1boYVLLG1Y+VQiGPu+m0\nL0dP+QmMfozefjeSS7JevEcWL8m/tEDs2sR/X8k94LXPs/RVdr9FjcYQvesBtB58pL9tF5b3dvCm\n21G39VYAkLdv0kDrv1Pr1iNqI7zrk9yiFgc1rKGJgMKxvu0WJqxCoBPxR13273vBYUIv04rz4rSd\ntZzVvLlYS50i73Py+j+abIHxzMhz9Fz3GedAphXITAbK+g0A7BQiJgHd9BwTry429s8WpL7ecGoW\npBfp3PesymOTz7Gh1MXsvL7c2FJnaedauUbeeR/th//Y4p3fo9PICbrgmlt3g7fehd7zLrG7pSC6\nAOwUHi3nWoe5TrGWk8Esj1YCHw0qdl92BVItUeOqT45kRkXSYZVQcRB0zPsAdaJ33o/NjvsRxLhx\nOZqvxMLXULfVlhh6OquNi1xxA2IPz4WyoRmf/O9TqN9ma/SeezESCxZh85/8WC+1EbLGELbsVhZV\n1XFgK2ju6GMlySkd2z2uADIRH3tPkH1ZRztrfw1dH1TF+PGQySSGm17D5EMPzr+wBE1kpq/f2AAP\nZE2w/5+9s46bo7j/+GdOntPH3aKEhBCCJRAkITgECQR3T/mhxd2lQCkSaHEoWrTQFigUaSBogUKN\nYiVIjPiTPMnjt78/7nZvZWZ3ZnfPnmferxfkub3ZmbmVmfnO11Jd3a52mUggYPmFNJM1LigLr4FV\nq9H7zXyUbTAy/bljDda/zKmpcoTPx9IJx8GMNhTkIwZRKoV1pqjhgDEoFi3EPe0716bupnc8tbrD\ndjOEpmEXcrsoVkpIa7zy8usRGjHMvpCIEGQq25dZqLpFEXl57J7bvn6qllIIvT++jWag650PvLVD\nwzTnsQRXLXK9YHAmS12qhQRL8MtYLC09/jT61+pz4EWIEByGqHORiLWA+dT/zUd4dHouWvfiK+h6\n5wPUXnOpVUBWN75p772iYPlFV6Lr9bes3zGwCF6C81R2XHU3jjtueug2+ilfIvOldqT7nQ/QN/87\ndL05Dx13P5gupQ9Aqj7bJsFIGRjAstPOQ3j0SDQ/lw2kQ41YrUvn5kv6QF29xQKJRMQ0kh41rpbn\ngBX1Wf2YKd/zL52PMWcXVME1Zfp96vOyMplA2fixSO6/N1d9qjBqp3HV2mbJb6mUK8VM6cz+AgsV\ndRdR4fVxZWlcMxdb6exkOqObE447ttXba3HoX33rb7Bw+t6GXWQ1vLoqGHf9NZ3I3LAQ1d3wVHcP\nNUASBqw+rgAcoyqvuul2629TFHTMucdSdoARvc/Qrv4Ft1s4mwaxrnnvY+kJp2PtE/YaUyaZRUHv\nl99gybGnYMUFV6BbH+ZcbdaD4KoFutAgWHnVjYb0NNzQTIUpzu9cUCaE/vnfY8mBR2sD5sprbsKq\nG937PDppR+2uq9Lbiz7eNALGRimV+RyWnoKSSlEFzpTet5x3AeQyqINwehva9R8EGtdSElwB8KfL\n4MD8Tq19lJ6OgBuBxZddChalr88h/7d/GNLI+YTS3Y1uXa5mmuBqiKgssOAmwSBTM7nq5jsN1lRd\nb7+H/kVLnCOWFiDfMC2wm5eAf4sPOFr7e8Wl12H9K29orkTUzT2G4CoitAIUDZCo8KS+By4FF4s5\nu6V+q1ZVg5IyJV3pALo/1fmJ699V9W917FDPVX2n/zdfKzrQsQYLd54JC7o51rOVhw79tfDLjNUt\nJOYshBkQiYlCw/zu8Pog655X3k3wQOa39X/3A9XVovOZF7Dyqhu56gKyz4BogDIDLtdBJTP7c+Wd\nMsEbnMm8AzGwbHk6/DTHA7H2t08I9Unp6RXSoJGyMgzoTXEzD7rS04v1upyoPx13Clbfdpe1glQK\nXe9YBTWnvKsADMnUASDEMidhTVz6QV0XVVjEZ7M/E8HQ7YCm+o6tf+V19P03bZJlNrkGYA1gtaoD\nA8vdpWFR+vqw/pXXhc/r/vSfVD9F5saAiWBTg6kj7EGhf+FirP3ds1DW8r0jVHisIBiCa2ptJ1Zc\nfRMW73eE9UsvO7A53L3t/dfnVL95/cYXtybVZT/7ddpdrmZ072bH3Q+h96tvPAX7Khbcmgr/sNlU\n3/1t/DCbE3ocfBZYRKJM9v6XYdaKzFjrRXAtAs3L0hPPyH5wmqdp3WVsLPX8+79aUEQLAwNYcdn1\nUBQFSiqFZWdckBboHBZ1vJutq26+g/2l4LKq+90Prf3o95ZHGIAxF6gmFOp+P0tYc4nXd1Y1uXVr\nOeMYnErJrpeMJw6gf8Fi6ndLDj8RPR9+Yl+t6uOqucFZn7GOO++lrkN+Oj67Hlz/+lwturSQxUaR\nw6M91OO7qbAW9ZluKqzS+fTzupM4TYUzQZQ6n/0DFs+krLsE0TSuHKbCQHpzpPcr48aX+ntV/3de\nSsdU2IXtO3dU4a5uDCxbjkBVJUg4jOXnXY6ez/6FyGabOJ4rbKbV2wuE+XcoSCiIldf8MtvXzK5t\nx533GfvBWFAoqRRWXX+L5ThvgCRWLjQe9Lvzhp16AbNvS7Jwxkvaa9F6ZopTdrlp5pw0c+qO+x9B\nzYWUEOgZWEEp1j7xDPMcO5Yedyr1OCtvoplgfZ0xEJONH9iqm++gap6F4BkwGTuS615+jT3JCkYN\nTZ+S+8mz75tv0UF5zvS+RGZfdyb5mut1i9uOux/EmoceQ2SrLfPUeA7xoHHtfu9vPnaEQ3viM7lK\n6s6F3YI/NSBuEaCnCARXPU7+urQxh5SVUf1Gu95w0Aj292PB1D0R3XKzdN2UOmjn8OAleBMPdvMM\ndx3rsms1ZWAA61/7qxa9GIAuHhHjvQ+FhMztPZu6quOqx3QoLDp+80D6D9NU13rrvei18UFmoaRS\nWHzA0Zqpb+/nX2L5pdei6tSTtDKpNWsRqChnxnFQBVUAxsBYfX3oevdDxLbbWrhfxYao4LreKa2R\nE7pn9ofNpiKSef/NGzR+5B7XnimPLD7keES3max95rUIVK0rhn02L3sw8x6J+r+Xzta7i4WKfjC0\nI9W5Dgt33R8rLrsOQFbDlQs/mlR3t5DGdf3rc9H/o86HTtSfhCE48GhcARi0jsStOQ1g1P7Z3UtL\nahnjRy0Co6nc6lut2ubuv32Cdc+/aO0WbWCm+QIG7BdhVA03YHF+z9eCzLxoXHLYicyybrXJ1kYZ\nf2dgaQVSa9bALL31fvkNej79J/oXuQmQJX6KX7haBOXBtBmg7Oj29HoLbFQsFJG5sytzd/OYIDJG\n5DQyuAcUFCQl0bKf5ybYn1OE5NRaazAgL2ZzSuc6S0oeO7reejcbmNF1o95OB4BUh7f0Gn3f/2i0\nKkqlsP61ufTCNGsthV/ro53i1Uoi5c3HlRvT+xTRCa1CsQoUBX3/m29QWKx/8VUs2vNA7bM6jtnO\nZ5T0a6tuvB3LTj0Xvd/Mp5xQWogKrl4xb0L2ZNzzRO+tyqpfzsGPU3blOo3Xks9wzoqV6Pvya6z9\n7RNMc/G+/83H+j+bLA51j/HiWUfpKnQ3l5WOxtXFQoU3aqeaU2j9m/PQ/9MyzTeRFqXTK0qXi4mj\nYQAAIABJREFUmODacdeDxvMF8v0BYKYC4NW46tsLs0ydmG0r9L9t7mXvF18h1d2DgDoRmRbZloiR\n2WSqlrqWzv45vVuUDQ2qgBUKGoIuuWVg1eocp6HJICKQ+NEf8yKVNoczdqSVrm6LD9eSQ45z35dC\namv6XCyC8tVfmlnpoBBci+c3uFkAeKGgGlc7FMXbhoLLd6LLTT5kDoiDZRQt1ZTbhW+foAsAgGyQ\nqALjNS/k4pmHmyqkBwYCQHVzUKCkNd3gd3txWhumHDYjNZNOr+lQnLDZCBKyMuIo2/vl1wiPGGbr\nv0piMS2ysJn+739AoLrKk5VeoRHdAPEMayw3jaP22Qyy93bt4/zWfgt33Id6vOP+R9Bx531o//Rt\ni6Z39Z33Zvu01phXWEXvt66iVwLqrVTtYibYUTyzvxM59MvquOe36T96e7Fo91me61tyzP8xv1O6\nuhwnRFsEFy0KU+MqLrgKw8jjarebtP6VN7Bgyi5Y+/Tzaf9W3h18gUGcGvmVpnH1Yvamo+OOe9FH\nCWqhsubxZ3wRkEWs6fu+cs7P6wcsgV3p6fEgvFl/qJbQ2svz6pIVV/IHNFBZdvalOeiJFer1FxH6\nfHoH/MYP0ynf8GUTQmD8KkBQHh4UJQXP6SyK6LaG2luEz9GbU4qQWiG4KVxE0DTPXuj98hvLc7Dq\nul+l/2DExxDVdKdWrWZa1HV/9CkWTNnF8fwfNpuKtU/9XqhdcdgvBO8aDgCXSfOq636FBdNm2McT\nsRnrlp9zaUkLrYCHQJguWfv0C/QvTNZ+toE+lbQmtOPe32qH1gtYbphZ88BjANIZC/oXLk7HhfjX\n5+kv+7Jzz/oXXwUArH3q946KGVYAwbVPPIOut98T7mPJCK65XKhw+ZMIYOeTqHR3ezMnEjQV7rj7\nIepx7kHPS444ndCs5pwFIVy78quuvwWLdj+AOrnQk3ILpO+h+D7T8126fD0oP6/vW7YZzepfznHX\nDk/DTrB+I+9v17+XrDzCFJRuD4IrAdYIBkXLKS40YN3v5iCdBw3ahCKgbScU07BiwC7XZN7xqHUR\nntuKVuPqMb9ukRHfk8/krqTxYdOFms3AAysuvhrrX33TcEyNekt9vvoHhDXdKy6+GstOO4/6Xc/f\nnTNF9GdiSXj2cfTAarugW2YE7nPPJ/9gfsebqaNU8RQh1wWdrI0PEcsVRcHyC68y+LAuP/NCrHEZ\nbV7VuA8s+QmL9joYANLBakHfCE8tX6mlCRSNNbLm3oex7IwLhPs4eGaZEiHV1e0pSbvogpcWBRXI\nk8ZVJ7R0f/hx9riA9rzr9bmWY50vvGQtKPC+0EyFqYtB14KrddDpMgWEUfr72Ynn3SIQrTl7DkMw\ncfHbqRs2LB/X7m7XiyZCCNO/WGKCcv2F/JuLVONaVHj0V1YURcxipFh9XFOpotKYeqaYtPq5wo/f\nmE83DVqu+r5ef9MwOcS2AJz9n/3CTTYNGo6plSQAnAOy5QuhwJmKYgjKqWKIPCxCZt3e+Xx2nd31\n5tvoX7AI6/9M36jRzIZzFKzMTMkIrm5toYsNpavbe5J2HxhYyrd4VXr9EVwNO3UeB2Oa1lkk2AI1\nqjClTseQ9QKYd2Y77noQSw49Ab1f+2iy62YRwtqY4BBc+39c6BixkhXZ25PG1aFvP2w2FesKuBNe\n7PQJBNHIV17OksbNotDLYr9INa793/84qIS9ojJHtyFQUe7+5DwFifMN/T3JCBmptes8+9ka4NkA\nzpdlgW/PoBRcuSjF+U5RqOb6XqPd9y8wnr9o70Psu9HTk7fAgSUjuA6WF0/p6sp75DIavBrXvi+/\ndt8IbXFGiGdzsnW//5NlwuVNfQQAqfW0dDjWxeC6F18R7xzgmJR65S9uReez6fDffpo8WlIHeanL\np4mZlXdUWb/evYkZR99WXHx11jxdYkAoJ3IpTuR5xuumqqiAVLTBmYBBkSNYo0QE1+j2U1yfy4qB\nUazo406o66g19/4WA0uX5aQNJiWmSFk9555Cd6EkKJXNKj193/2A1OoO3+vttYnLYia1vgs/br2L\nJZhsrhhEs0xp4NVU2C+EFq++Nqx43q3s+998/HTMKeaK+buwltNU2CW9n39h+33nU7/XhDaFIkS7\nxs8UIW7MjgXofv8j1+f2fPwpV7mfjpztug1JGr8ClA1qXGhPLVpvkSqK1VQY8GwqXEifQQtFlHLJ\nFi97+oysA0WLTrAg0Rz4I/KuT/L1DgYIUj7EYFn/0l986EzuIYl4Qdvv+dd/Ctq+G7r+mpuo6iIB\n41IrVwFguPHlAF9Wp4SQPQghXxJCviGEXEj5nhBC5mS+/ychZAvhNgbJAko0Hc6gQ1H82clWdzzV\nugR2jqnpcAqkxVhxybX+VebnbuFg0pxI3CM1rs64WMQuPfks180VrY8rUFRpirxTGoIry++Mi1Lz\nfdRtqKZE0/NxwBt8KH/vIMFKStqlwUqgoqKg7dN8RYud3m/ykyHCDqUrowjL0/jvuRVCSBDArwHs\nCWA8gMMIIeNNxfYEMCbz32wA4pFVBskCSunqynvI7aJCUXIiFCkCvjrKesoOZpGmmBDCx+tKcqxx\nLTkGyfgjil1UYZJM5rEnxUvXPPFw/hZEtLZFPFb56a5QcErQbFCUkosdkocN1dW3cyxP87h51Pf1\nt3lrq9B48tceovR9QXfnI+X5m5/7fky7hAWrq/LSnh+jwFYAvlEU5VtFUXoBPAlgpqnMTACPKGk+\nAFBFCGkWaWQwaVwH09wuitLd46tQ1Puf/6Lv+x887xx7ip5cLPho2pbqKpApeZESqCzsTnDBsBl3\nGx8QSMcwiFE8viuiKQSKeqwaTHPbEBBcC5H32gt5yXfLsTGUr1zKPZ98Vvwm6z5q2QKVUnD1C2Ut\nPaNILlAzSvR9k59NFj+euFYA+uy4CzLHRMvYM0g0QKlC+ZbmmPIjD+YqN9DR4ftA3PXmPM/BEoo6\n4Akvfi60BKI0DwUCyUShu1AQBlNezlzhS4Abn/IsFpxB9LyUYqAWUQZyENQlp+Qz9Y4NXjerRGBp\n1IqF2l9c7ltdZlNhEo/5Vrdk8FB0swwhZDYh5GNCyMf64x995XPOywKxavESLFroXyTZYuF/A3w7\nt71ff4vuzyj5Pr20PX8+umi5WQXo8DEqYaFYsTIPu9FDlPWDZMNpQDD4RadNYJCPP3YfYGsw0bnG\nZXTsDCtWrMAHH/Dn5y5YYD0OFi9ZUugu+MbHn3xS6C7kHF6fzmJh6bLi8EFcdcOthe5C0fCv77/z\nra6f1hm1hP1FslEhKS78EFwXAmjXfW7LHBMtAwBQFOVeRVEmKYoySX98+wP296GrhacyEkVLs5CV\ndEkwfku+eFtkYADEZ/+Q0WPGIBqJeqojWWJpAWjU1dUVuguDlkRicGhcqw7YV6h80sZPZtLkyV67\nMyhIxrxpBWprazFlytY+9aawNLe0IHmQ0VOo4Z7SXORP2mqrQndBYqK+prbQXZCY2GzLLW2/D284\n2nIs2EpfA7dtNNZ4brTwqSMlxYcfgutHAMYQQkYSQsoAHArgj6YyfwRwdCa68BQAHYqiLOZtoOl3\n9/vQTX7KNt5IqHzTE/z9UygajKpzThVqrygppIlYIOA5kfrA8hU+daaADCIzvaKjyMwGW1551t2J\nws9I4X53qL3N9ns342Z060nOhQTxHOCm1ALk2EEIai4513AoF9c8LwwS96TBRFH7dw9RiEPgwqbf\nPWA5FqytoZa1RBUeJLFtJP7ieWRWFKUfwGkAXgXwXwBPK4ryH0LIyYSQkzPFXgbwLYBvANwHwJyE\n0xaS2dGuPONnXrvLRWKfPYTKl40fi6rzzuAqm+rqNgTjKJs4AWXjNrSUC9ZntWckEQd0kYhDo4YL\n9S8vFHKA6e/HwOKfPFVBjTRcAJIHe7AsKDLhalDB4ZddeepJeehImlBTo6vziKh/eSGfKYemK446\nVLjKss02cdkZG7xakAwMeMvFWUQMJr/QwerfHWxsKHQX3FOimzzhMaMK3YXc4SC40gKr9v6Tni81\nUFVpPHeIRvP34x0dFAoxBr6MzIqivKwoyoaKooxWFOW6zLG7FUW5O/O3oijKqZnvN1EU5WP7Gk1k\nJsNA1Js5KD/iqwjeBaHS3WUIMKD09FAXh3qn9GBjPYb97Q1UnHh0+nOeQk6LUMgFS76SHucDxxy/\nYZvvB8+asfjgeb4ZRZKHHeBvX7zgUzqJxP57+1KPLTkYU+zS+7jFa4TRos7LKoqPgfeCLQV2qcmT\nxjWx/145b0NdOwDiG/NFRYm69NRedxliO2xX6G7kBBL2T7i0pMMZqhpXH3532YYb+NAR/6k4/gjt\n77LxY21KsimNLcUc7nzGdtkBjQ/fheSBOr8cNw7hnIssczS6VEcH/ffp+qDlxsu0ERpmb0Lnheh2\nU1B36/ViJxFS0AGmf/73BWvbdxyePTvBlgSG6CDvAb1lgz0c7zfj1tVc8HPu/uQc0bGN8bPDo0bY\njnlJQV/a/JGD3R2vWqDBJLgyrq+bBUogj3kI6R3Iz3hKIrn340vMnJHzNvKBSL72YkLp7YPS3VPo\nbuQEP7Wi5rRzImua8AZFpNX2uOnqR/pPLy4asV2me26fRXyPXbS/qy8+x1UdJSG45jKHa9mGGyCy\n6QTUXHquc2HYmenyalx7DAudVMdaurZSv75Uv8/8E2psRM2VF3K1J0rPJ58ivuNUtLz4FPc5gaoK\n6V/pE07aG1uNrNS4ClN+xEF8BTkmIlro/uh26aA75YfT20ketB9f+x4I1mcDmghr9wQn4Ib75qDh\nwTsR32s3sXZ8aLtQDKxa7el8pX9AOJdr8UL/HW6e80KnoPLbVLj8qEN8rU8Evyyiaq68UGCzLwd4\nzNdeKIJ1NVBKIMVc83OPcJUzrIM9CK7RbY0B0MybVYFqo+mwbZ9GtDsXyhOBmmruspGtKcGtCuBf\nr3dTq7/5mtw1pNuMiEzYCPEZu4pX4Wd/ckVOJzDd5NT0xP1oevJBW0th5qAtYCKlT2egdHUxhD5d\nJ7RJJ/cLOW1XUGCiC1RVifvOSeg45JMlITvBVd4DUcqPOYxPeOV4vqObT0TN5ecbjqm7wKHh9ElV\n6WcHG4lM5ovU7YgH82DmgpdxPDp5c0S32LR4n8VcdMvrgtSjqTEANP/hCc91VByXNeGKTnEZMdpH\nuaLgGlfz4lEXZ8IVRewvzkt8tx0Lu0mdEn9X9Bt3hSLU1Jh2C+Mt7xCYzg/C48ZYjrnxrTQrloKN\nDWh9/QW+c03vFDG5Qpnn01JBRAsdHmFVhuXSv772hiuox4MN/m1IJfbZA40P34XWuS9avrMoX1zM\nGSUhuJIcCq76l65s/FiUjRvDvftteMk5JiVVdb/+1TdNnXA4N/N1xVGHILHPHpaFdk78zQRenNi0\nbaXGlUF49Eih8o5RE201rvIeiMKrieAqR4DkrH2MxxzGkth2U5jfNfzmZp6uOaMTukPNTcxiNZed\nRznqbsWrP8t1oIlcbIYVoUCtDPS7c0/REShPovL02Z7qiEzaHAAQbG5C/R03uarDT3/dQDI3gmv1\nhXym+yQcNgjzThsUpKhTd/j03Bf6/SlRH1cAUHr4N7iqL+J7Rss2Ge+2OyBllOdVN+aysnlYtKAm\nIa3i+CMRrOPbLFAGBozPVCCAqrOzQYUC5eWUs4qfUJuAfz5t7cyhcW165rcAZ8yG8KgR2t8Jnamu\noRumHO9xRjkztICiweZGRDadgKAu2FbdLdeh5ooLrMo/F3NfSax0cxrdz8NA3PS7+9H42L3c9ZjN\nIlQCtGBL+puZEUgC5UnUXnOJ1ZwiFzvTApelbPw4sROKEJ5FR+31lwvXW3XOaULllT4Hjavdrn9p\n34LC4ZeWyG7jgOUrOmYUwhtZo4oD1t1nM3W/vJqrW7VXX6z9HaWZJWWg+qXaaVztxrzMdyQeM5if\niZgZklw80IVeeFMY+Gkp1v/lTeeCNgQScUQ2neCtI7p51nXAlcy8VXvjVd76AiBQk78ghHqtXNmE\njVB77SUI1taIRaF2cmkqqMZV17anTZLCvj+iqaeannzQoojQB6riJTzWqp3kRc1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6v0AczKaM8F/ffGpm+PYH0dYnr/czeXWFGMwZk4NkX1eZNZMR8sWlHzfeN4B+rvusXic2jngqKO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\nRbNwlSRJkiQVzcJVkiRJklS0/weqULgawrrf5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd5eceddd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrets.SHINDEX.plot(grid='on',color = '#E12F3C',title='Shanghai Index Returns',figsize=(16,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fd5cd95320>"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2thHu4aVpqF3BiXaujZFzRbuV7uVAZmNXHa5b9xIA4KenXJqyerrGoxs0pf3x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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd5cd8a198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfrets.SZINDEX.plot(grid='on',color = '#00AC73',title='Shenzhen Index Returns',figsize=(16,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1fd609bc5c0>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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8c/XNVbzq+bvQ9TTlSffu8R9eQ4ZEl61UVNEoGVFfDz/8YezamUTU1GQ+v2CM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\niqIoeUUVjaIoipJXVNEoiqIoeeX/B7W2111QTQL7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd5d19cf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.subplot(2,1,1)\n",
    "df.USDINDEX.plot(grid='on',color = '#8989FF',title='USD Index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dfrets.to_excel(\"yyfdataout/yf_data_returns.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SP500</th>\n",
       "      <th>USDRMB</th>\n",
       "      <th>SHINDEX</th>\n",
       "      <th>SZINDEX</th>\n",
       "      <th>USDINDEX</th>\n",
       "      <th>EURUSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4441.000000</td>\n",
       "      <td>4305.000000</td>\n",
       "      <td>4274.000000</td>\n",
       "      <td>4274.000000</td>\n",
       "      <td>4445.000000</td>\n",
       "      <td>4592.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1413.358131</td>\n",
       "      <td>7.261654</td>\n",
       "      <td>2390.367939</td>\n",
       "      <td>7936.923814</td>\n",
       "      <td>110.963164</td>\n",
       "      <td>1.216617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>402.768955</td>\n",
       "      <td>0.851344</td>\n",
       "      <td>915.039787</td>\n",
       "      <td>3992.749709</td>\n",
       "      <td>10.060243</td>\n",
       "      <td>0.175403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>676.530000</td>\n",
       "      <td>6.093000</td>\n",
       "      <td>1011.499000</td>\n",
       "      <td>2622.026000</td>\n",
       "      <td>93.757100</td>\n",
       "      <td>0.826800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1131.420000</td>\n",
       "      <td>6.461600</td>\n",
       "      <td>1667.578750</td>\n",
       "      <td>3820.805250</td>\n",
       "      <td>101.847500</td>\n",
       "      <td>1.099875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1309.720000</td>\n",
       "      <td>6.879800</td>\n",
       "      <td>2199.461000</td>\n",
       "      <td>8235.478000</td>\n",
       "      <td>110.025600</td>\n",
       "      <td>1.254100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1562.170000</td>\n",
       "      <td>8.276600</td>\n",
       "      <td>2976.678750</td>\n",
       "      <td>10701.904750</td>\n",
       "      <td>119.976400</td>\n",
       "      <td>1.343250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2480.910000</td>\n",
       "      <td>8.279900</td>\n",
       "      <td>6092.057000</td>\n",
       "      <td>19531.155000</td>\n",
       "      <td>130.242000</td>\n",
       "      <td>1.599800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             SP500       USDRMB      SHINDEX       SZINDEX     USDINDEX  \\\n",
       "count  4441.000000  4305.000000  4274.000000   4274.000000  4445.000000   \n",
       "mean   1413.358131     7.261654  2390.367939   7936.923814   110.963164   \n",
       "std     402.768955     0.851344   915.039787   3992.749709    10.060243   \n",
       "min     676.530000     6.093000  1011.499000   2622.026000    93.757100   \n",
       "25%    1131.420000     6.461600  1667.578750   3820.805250   101.847500   \n",
       "50%    1309.720000     6.879800  2199.461000   8235.478000   110.025600   \n",
       "75%    1562.170000     8.276600  2976.678750  10701.904750   119.976400   \n",
       "max    2480.910000     8.279900  6092.057000  19531.155000   130.242000   \n",
       "\n",
       "            EURUSD  \n",
       "count  4592.000000  \n",
       "mean      1.216617  \n",
       "std       0.175403  \n",
       "min       0.826800  \n",
       "25%       1.099875  \n",
       "50%       1.254100  \n",
       "75%       1.343250  \n",
       "max       1.599800  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SP500</th>\n",
       "      <th>USDRMB</th>\n",
       "      <th>SHINDEX</th>\n",
       "      <th>SZINDEX</th>\n",
       "      <th>USDINDEX</th>\n",
       "      <th>EURUSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4091.000000</td>\n",
       "      <td>4091.000000</td>\n",
       "      <td>4091.000000</td>\n",
       "      <td>4091.000000</td>\n",
       "      <td>4091.000000</td>\n",
       "      <td>4091.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.015030</td>\n",
       "      <td>-0.005235</td>\n",
       "      <td>0.034246</td>\n",
       "      <td>0.045117</td>\n",
       "      <td>0.003125</td>\n",
       "      <td>0.005756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.210493</td>\n",
       "      <td>0.106656</td>\n",
       "      <td>1.604210</td>\n",
       "      <td>1.799297</td>\n",
       "      <td>0.310703</td>\n",
       "      <td>0.636947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-9.034980</td>\n",
       "      <td>-2.011720</td>\n",
       "      <td>-8.840626</td>\n",
       "      <td>-9.289852</td>\n",
       "      <td>-2.275154</td>\n",
       "      <td>-2.728324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.508803</td>\n",
       "      <td>-0.023634</td>\n",
       "      <td>-0.693534</td>\n",
       "      <td>-0.821900</td>\n",
       "      <td>-0.164869</td>\n",
       "      <td>-0.370007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.048817</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.066510</td>\n",
       "      <td>0.048859</td>\n",
       "      <td>0.001699</td>\n",
       "      <td>0.008295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.567063</td>\n",
       "      <td>0.016144</td>\n",
       "      <td>0.792535</td>\n",
       "      <td>0.921329</td>\n",
       "      <td>0.162739</td>\n",
       "      <td>0.360728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10.789002</td>\n",
       "      <td>1.857362</td>\n",
       "      <td>9.857043</td>\n",
       "      <td>9.998804</td>\n",
       "      <td>1.751054</td>\n",
       "      <td>3.819258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             SP500       USDRMB      SHINDEX      SZINDEX     USDINDEX  \\\n",
       "count  4091.000000  4091.000000  4091.000000  4091.000000  4091.000000   \n",
       "mean      0.015030    -0.005235     0.034246     0.045117     0.003125   \n",
       "std       1.210493     0.106656     1.604210     1.799297     0.310703   \n",
       "min      -9.034980    -2.011720    -8.840626    -9.289852    -2.275154   \n",
       "25%      -0.508803    -0.023634    -0.693534    -0.821900    -0.164869   \n",
       "50%       0.048817     0.000000     0.066510     0.048859     0.001699   \n",
       "75%       0.567063     0.016144     0.792535     0.921329     0.162739   \n",
       "max      10.789002     1.857362     9.857043     9.998804     1.751054   \n",
       "\n",
       "            EURUSD  \n",
       "count  4091.000000  \n",
       "mean      0.005756  \n",
       "std       0.636947  \n",
       "min      -2.728324  \n",
       "25%      -0.370007  \n",
       "50%       0.008295  \n",
       "75%       0.360728  \n",
       "max       3.819258  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfrets.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4091\n",
      "1.79907721749 0.0451171825694\n"
     ]
    },
    {
     "data": {
      "image/png": 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EdAFXADfVzxARi4AvA2/IzPtaX6YkSZI0tkYcSpGZRyPiGuBWoBO4ITM3RMTVxePXAe8D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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd57ea1320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xx=np.array([dfrets.SZINDEX])\n",
    "print(np.size(xx))\n",
    "print(xx.std(),xx.mean())\n",
    "\n",
    "from scipy import stats\n",
    "from statsmodels.graphics.api import qqplot\n",
    "import statsmodels.api as sm\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1 = fig.add_subplot(211)\n",
    "fig = sm.graphics.tsa.plot_acf(dfrets.SZINDEX, lags=40, ax=ax1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1 = fig.add_subplot(211)\n",
    "fig = sm.graphics.tsa.plot_acf(dfrets.SZINDEX, lags=40, ax=ax1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Y4xNZdZMkSZKek7q5Ynw7cHpEnEYtEF8AvKWxQEScAnwVuCgz7+97K4fU+ERy0WdvY/2W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\nDMaSJEkSYDCWJEmSAIOxJEmSBMD/B32XDntByRoYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd59661940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp=(dfrets.SZINDEX)*(dfrets.SZINDEX)\n",
    "tmp.head()\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1 = fig.add_subplot(211)\n",
    "fig = sm.graphics.tsa.plot_acf(tmp, lags=40, ax=ax1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1fd5e64c0f0>"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5g9a8pjjLPy9/jv3VwRQOjLImF7W2XRX7ljdoXfvplWPf28rUkpNTOegUlnlO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\njuM4jtNG/APhjbukehdidAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd5e4e2ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import acf\n",
    "\n",
    "SZ_acf=acf(dfrets.SZINDEX, nlags=200)\n",
    "SZ_acf2=acf(tmp, nlags=200)\n",
    "\n",
    "plt.figure(figsize=(8,7),dpi=980)\n",
    "\n",
    "p1 = plt.subplot(2,1,1)\n",
    "p1.grid(True)\n",
    "p1.plot(SZ_acf[1:],color='#009CD1')\n",
    "p1.set_title('ACF of Returns',fontsize=10)\n",
    "\n",
    "p2 = plt.subplot(2,1,2)\n",
    "p2.grid(True)\n",
    "p2.plot(SZ_acf2[1:],color='#8E008D')\n",
    "p2.set_title('ACF of Returns$^{2}$',fontsize=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2000-01-05   -0.308116\n",
       "2000-01-06    4.845100\n",
       "2000-01-07    4.728634\n",
       "2000-01-10    2.441040\n",
       "2000-01-11   -5.219963\n",
       "Name: SZINDEX, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfrets.SZINDEX.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.474994010000003"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " 4.845100* 4.845100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "object too deep for desired array",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-52-f79cf9a92d74>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      8\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[0myy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mestimated_autocorrelation\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mxx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-52-f79cf9a92d74>\u001b[0m in \u001b[0;36mestimated_autocorrelation\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mvar_x\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m     \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcorrelate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'full'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m     \u001b[1;31m#assert N.allclose(r, N.array([(x[:n-k]*x[-(n-k):]).sum() for k in range(n)]))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mr\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvar_x\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\site-packages\\numpy\\core\\numeric.py\u001b[0m in \u001b[0;36mcorrelate\u001b[1;34m(a, v, mode)\u001b[0m\n\u001b[0;32m    973\u001b[0m     \"\"\"\n\u001b[0;32m    974\u001b[0m     \u001b[0mmode\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_mode_from_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 975\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mmultiarray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcorrelate2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    976\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    977\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: object too deep for desired array"
     ]
    }
   ],
   "source": [
    "def estimated_autocorrelation(x):\n",
    "    n = np.size(x)\n",
    "    var_x = x.var()\n",
    "    x = x-x.mean()\n",
    "    r = np.correlate(x, x, mode = 'full')[-n:]\n",
    "    #assert N.allclose(r, N.array([(x[:n-k]*x[-(n-k):]).sum() for k in range(n)]))\n",
    "    result = r/(var_x*(np.arange(n, 0, -1)))\n",
    "    return result\n",
    "\n",
    "yy = estimated_autocorrelation(xx)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "np.correlate?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def gjr_garch_likelihood(parameters, data, sigma2, out = None):\n",
    "    mu = parameters[0]\n",
    "    omega = parameters[1]\n",
    "    alpha = parameters[2]\n",
    "    gamma = parameters[3]\n",
    "    beta = parameters[4]\n",
    "    \n",
    "    T = np.size(data,0)\n",
    "    #print('What is T=',T)\n",
    "    eps = data - mu\n",
    "    # Data and Sigma2 are T by 1 vectors\n",
    "    for t in range(1,T):\n",
    "        sigma2[t]=(omega+alpha*eps[t-1]**2+gamma*eps[t-1]**2 * (eps[t-1]<0)+beta*sigma2[t-1])\n",
    "        \n",
    "    logliks = 0.5*(np.log(2*np.pi)+np.log(sigma2)+eps**2/sigma2)\n",
    "    loglik = np.sum(logliks)\n",
    "    \n",
    "    if out is None:\n",
    "        return loglik\n",
    "    else:\n",
    "        return loglik, logliks, np.copy(sigma2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>volatility</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>28.562957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06</th>\n",
       "      <td>27.316475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07</th>\n",
       "      <td>29.221746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-10</th>\n",
       "      <td>30.700308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-11</th>\n",
       "      <td>29.996904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-12</th>\n",
       "      <td>40.697374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-13</th>\n",
       "      <td>42.148820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-14</th>\n",
       "      <td>40.290507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-18</th>\n",
       "      <td>38.813187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-19</th>\n",
       "      <td>37.118608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-20</th>\n",
       "      <td>35.406215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-21</th>\n",
       "      <td>34.055330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-24</th>\n",
       "      <td>32.520032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-25</th>\n",
       "      <td>31.068396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-26</th>\n",
       "      <td>29.651348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-27</th>\n",
       "      <td>28.284490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-28</th>\n",
       "      <td>28.074088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-14</th>\n",
       "      <td>27.832324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-15</th>\n",
       "      <td>36.896686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-16</th>\n",
       "      <td>35.403753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-17</th>\n",
       "      <td>33.921702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-18</th>\n",
       "      <td>36.956471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-22</th>\n",
       "      <td>35.271595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-23</th>\n",
       "      <td>39.201049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-24</th>\n",
       "      <td>40.296543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-25</th>\n",
       "      <td>39.608191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-28</th>\n",
       "      <td>37.769850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-29</th>\n",
       "      <td>38.574134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-03-01</th>\n",
       "      <td>36.705946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-03-02</th>\n",
       "      <td>35.680224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-10</th>\n",
       "      <td>12.150096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-11</th>\n",
       "      <td>12.318112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-12</th>\n",
       "      <td>12.235196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-13</th>\n",
       "      <td>11.996254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-14</th>\n",
       "      <td>11.735586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-17</th>\n",
       "      <td>11.714237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-18</th>\n",
       "      <td>22.940804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-19</th>\n",
       "      <td>21.982289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-20</th>\n",
       "      <td>21.656962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21</th>\n",
       "      <td>20.819679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-24</th>\n",
       "      <td>19.960040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-25</th>\n",
       "      <td>19.172113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-26</th>\n",
       "      <td>18.645107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-27</th>\n",
       "      <td>18.203687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-28</th>\n",
       "      <td>17.680183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-31</th>\n",
       "      <td>17.044106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>16.501860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-02</th>\n",
       "      <td>15.918687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-03</th>\n",
       "      <td>15.693919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-04</th>\n",
       "      <td>15.290138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-07</th>\n",
       "      <td>15.368217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-08</th>\n",
       "      <td>15.027690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-09</th>\n",
       "      <td>14.578720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-10</th>\n",
       "      <td>14.168575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-11</th>\n",
       "      <td>14.201068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-14</th>\n",
       "      <td>17.125962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-15</th>\n",
       "      <td>17.546605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-16</th>\n",
       "      <td>16.914527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17</th>\n",
       "      <td>16.326046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-18</th>\n",
       "      <td>15.798895</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4091 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            volatility\n",
       "Date                  \n",
       "2000-01-05   28.562957\n",
       "2000-01-06   27.316475\n",
       "2000-01-07   29.221746\n",
       "2000-01-10   30.700308\n",
       "2000-01-11   29.996904\n",
       "2000-01-12   40.697374\n",
       "2000-01-13   42.148820\n",
       "2000-01-14   40.290507\n",
       "2000-01-18   38.813187\n",
       "2000-01-19   37.118608\n",
       "2000-01-20   35.406215\n",
       "2000-01-21   34.055330\n",
       "2000-01-24   32.520032\n",
       "2000-01-25   31.068396\n",
       "2000-01-26   29.651348\n",
       "2000-01-27   28.284490\n",
       "2000-01-28   28.074088\n",
       "2000-02-14   27.832324\n",
       "2000-02-15   36.896686\n",
       "2000-02-16   35.403753\n",
       "2000-02-17   33.921702\n",
       "2000-02-18   36.956471\n",
       "2000-02-22   35.271595\n",
       "2000-02-23   39.201049\n",
       "2000-02-24   40.296543\n",
       "2000-02-25   39.608191\n",
       "2000-02-28   37.769850\n",
       "2000-02-29   38.574134\n",
       "2000-03-01   36.705946\n",
       "2000-03-02   35.680224\n",
       "...                ...\n",
       "2017-07-10   12.150096\n",
       "2017-07-11   12.318112\n",
       "2017-07-12   12.235196\n",
       "2017-07-13   11.996254\n",
       "2017-07-14   11.735586\n",
       "2017-07-17   11.714237\n",
       "2017-07-18   22.940804\n",
       "2017-07-19   21.982289\n",
       "2017-07-20   21.656962\n",
       "2017-07-21   20.819679\n",
       "2017-07-24   19.960040\n",
       "2017-07-25   19.172113\n",
       "2017-07-26   18.645107\n",
       "2017-07-27   18.203687\n",
       "2017-07-28   17.680183\n",
       "2017-07-31   17.044106\n",
       "2017-08-01   16.501860\n",
       "2017-08-02   15.918687\n",
       "2017-08-03   15.693919\n",
       "2017-08-04   15.290138\n",
       "2017-08-07   15.368217\n",
       "2017-08-08   15.027690\n",
       "2017-08-09   14.578720\n",
       "2017-08-10   14.168575\n",
       "2017-08-11   14.201068\n",
       "2017-08-14   17.125962\n",
       "2017-08-15   17.546605\n",
       "2017-08-16   16.914527\n",
       "2017-08-17   16.326046\n",
       "2017-08-18   15.798895\n",
       "\n",
       "[4091 rows x 1 columns]"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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X6Bq6FOgSHs3LJcRAmRGBbil8oQv0HupXjEiBLukfSIEuEaHZ0IMh3YYORCZLNZo/VPzQ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\n1zyvobet3as2Z4Y+2402LcfSikKYRm0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3l/m3XbV6FcJ1kReh031XUlICajNeb42G5kbD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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd641c1a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "startingVals = np.array([dfrets.SZINDEX.mean(),\n",
    "                       dfrets.SZINDEX.var()*.01,\n",
    "                       .03,.09,.90])\n",
    "T=len(dfrets.SZINDEX);\n",
    "sigma2 = np.ones(T)*(dfrets.SZINDEX).var()\n",
    "#estimates\n",
    "#np.size(sigma2)\n",
    "loglik0, logliks, sigma2final = gjr_garch_likelihood(startingVals,dfrets.SZINDEX, sigma2, out=True)\n",
    "\n",
    "vol = pd.DataFrame(np.sqrt(252*sigma2),index=dfrets.index,columns=['volatility'])\n",
    "%matplotlib inline\n",
    "vol.plot(grid='on',color = '#CC0066',title='SZ volatility with GJR')\n",
    "\n",
    "vol.describe()\n",
    "vol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.    (Exit mode 0)\n",
      "            Current function value: 7709.5900557058085\n",
      "            Iterations: 15\n",
      "            Function evaluations: 122\n",
      "            Gradient evaluations: 15\n",
      "Initial Values= [ 0.04511718  0.0323747   0.03        0.09        0.9       ]\n",
      "Estimated Values= [ 0.01553818  0.03374574  0.05451845  0.03292522  0.91978903]\n"
     ]
    }
   ],
   "source": [
    "from numpy.linalg import inv\n",
    "from scipy.optimize import fmin_slsqp\n",
    "\n",
    "def gjr_constraint(parameters, data, sigma2, out=None):\n",
    "    alpha = parameters[2]\n",
    "    gamma = parameters[3]\n",
    "    beta = parameters[4]\n",
    "    return np.array([1-alpha-gamma/2-beta])\n",
    "\n",
    "finfo=np.finfo(np.float64)\n",
    "\n",
    "bounds  =[(-10*dfrets.SZINDEX.mean(),10*dfrets.SZINDEX.mean()),\n",
    "         (finfo.eps,2*dfrets.SZINDEX.var()),\n",
    "         (0.0,1.0),(0.0,1.0),(0.0,1.0)]\n",
    "args = (np.asarray(dfrets.SZINDEX),sigma2)\n",
    "estimates = fmin_slsqp(gjr_garch_likelihood, startingVals, f_ieqcons=gjr_constraint, bounds=bounds, args =args)\n",
    "print('Initial Values=',startingVals)\n",
    "print('Estimated Values=',estimates)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initial loglik= 7794.836719735496 ested loglik= 7709.59005570583\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>volatility</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28.562957</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   volatility\n",
       "0   28.562957"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fpaFnEDKb6PYOd3GvFckj2QJdZnKx+qvzMogmnkzUxhSJg5tSAizgqIUrDT3D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\nxX3fOcual+GWzbeYBul5iGXewMWioctMLofnmye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3/vi9V/1q7a6iqt7r9n7OqdNV7/2q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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1fd60a62748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "loglik, logliks, sigma2final = gjr_garch_likelihood(estimates,dfrets.SZINDEX, sigma2, out=True)\n",
    "\n",
    "vol2 = pd.DataFrame(np.sqrt(252*sigma2),index=dfrets.index,columns=['volatility'])\n",
    "%matplotlib inline\n",
    "vol2.plot(grid='on',color = '#32CD32',title='SZ volatility with estimated GJR')\n",
    "print('initial loglik=',loglik0,'ested loglik=',loglik)\n",
    "vol2.describe()\n",
    "\n",
    "vol.merge(vol2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>volatility</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>28.562957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-06</th>\n",
       "      <td>27.316475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-07</th>\n",
       "      <td>29.221746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-10</th>\n",
       "      <td>30.700308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-11</th>\n",
       "      <td>29.996904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-12</th>\n",
       "      <td>40.697374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-13</th>\n",
       "      <td>42.148820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-14</th>\n",
       "      <td>40.290507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-18</th>\n",
       "      <td>38.813187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-19</th>\n",
       "      <td>37.118608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-20</th>\n",
       "      <td>35.406215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-21</th>\n",
       "      <td>34.055330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-24</th>\n",
       "      <td>32.520032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-25</th>\n",
       "      <td>31.068396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-26</th>\n",
       "      <td>29.651348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-27</th>\n",
       "      <td>28.284490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-28</th>\n",
       "      <td>28.074088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-14</th>\n",
       "      <td>27.832324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-15</th>\n",
       "      <td>36.896686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-16</th>\n",
       "      <td>35.403753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-17</th>\n",
       "      <td>33.921702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-18</th>\n",
       "      <td>36.956471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-22</th>\n",
       "      <td>35.271595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-23</th>\n",
       "      <td>39.201049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-24</th>\n",
       "      <td>40.296543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-25</th>\n",
       "      <td>39.608191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-28</th>\n",
       "      <td>37.769850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-29</th>\n",
       "      <td>38.574134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-03-01</th>\n",
       "      <td>36.705946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-03-02</th>\n",
       "      <td>35.680224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-10</th>\n",
       "      <td>12.150096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-11</th>\n",
       "      <td>12.318112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-12</th>\n",
       "      <td>12.235196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-13</th>\n",
       "      <td>11.996254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-14</th>\n",
       "      <td>11.735586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-17</th>\n",
       "      <td>11.714237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-18</th>\n",
       "      <td>22.940804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-19</th>\n",
       "      <td>21.982289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-20</th>\n",
       "      <td>21.656962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21</th>\n",
       "      <td>20.819679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-24</th>\n",
       "      <td>19.960040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-25</th>\n",
       "      <td>19.172113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-26</th>\n",
       "      <td>18.645107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-27</th>\n",
       "      <td>18.203687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-28</th>\n",
       "      <td>17.680183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-31</th>\n",
       "      <td>17.044106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>16.501860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-02</th>\n",
       "      <td>15.918687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-03</th>\n",
       "      <td>15.693919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-04</th>\n",
       "      <td>15.290138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-07</th>\n",
       "      <td>15.368217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-08</th>\n",
       "      <td>15.027690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-09</th>\n",
       "      <td>14.578720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-10</th>\n",
       "      <td>14.168575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-11</th>\n",
       "      <td>14.201068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-14</th>\n",
       "      <td>17.125962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-15</th>\n",
       "      <td>17.546605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-16</th>\n",
       "      <td>16.914527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-17</th>\n",
       "      <td>16.326046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-18</th>\n",
       "      <td>15.798895</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4091 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            volatility\n",
       "Date                  \n",
       "2000-01-05   28.562957\n",
       "2000-01-06   27.316475\n",
       "2000-01-07   29.221746\n",
       "2000-01-10   30.700308\n",
       "2000-01-11   29.996904\n",
       "2000-01-12   40.697374\n",
       "2000-01-13   42.148820\n",
       "2000-01-14   40.290507\n",
       "2000-01-18   38.813187\n",
       "2000-01-19   37.118608\n",
       "2000-01-20   35.406215\n",
       "2000-01-21   34.055330\n",
       "2000-01-24   32.520032\n",
       "2000-01-25   31.068396\n",
       "2000-01-26   29.651348\n",
       "2000-01-27   28.284490\n",
       "2000-01-28   28.074088\n",
       "2000-02-14   27.832324\n",
       "2000-02-15   36.896686\n",
       "2000-02-16   35.403753\n",
       "2000-02-17   33.921702\n",
       "2000-02-18   36.956471\n",
       "2000-02-22   35.271595\n",
       "2000-02-23   39.201049\n",
       "2000-02-24   40.296543\n",
       "2000-02-25   39.608191\n",
       "2000-02-28   37.769850\n",
       "2000-02-29   38.574134\n",
       "2000-03-01   36.705946\n",
       "2000-03-02   35.680224\n",
       "...                ...\n",
       "2017-07-10   12.150096\n",
       "2017-07-11   12.318112\n",
       "2017-07-12   12.235196\n",
       "2017-07-13   11.996254\n",
       "2017-07-14   11.735586\n",
       "2017-07-17   11.714237\n",
       "2017-07-18   22.940804\n",
       "2017-07-19   21.982289\n",
       "2017-07-20   21.656962\n",
       "2017-07-21   20.819679\n",
       "2017-07-24   19.960040\n",
       "2017-07-25   19.172113\n",
       "2017-07-26   18.645107\n",
       "2017-07-27   18.203687\n",
       "2017-07-28   17.680183\n",
       "2017-07-31   17.044106\n",
       "2017-08-01   16.501860\n",
       "2017-08-02   15.918687\n",
       "2017-08-03   15.693919\n",
       "2017-08-04   15.290138\n",
       "2017-08-07   15.368217\n",
       "2017-08-08   15.027690\n",
       "2017-08-09   14.578720\n",
       "2017-08-10   14.168575\n",
       "2017-08-11   14.201068\n",
       "2017-08-14   17.125962\n",
       "2017-08-15   17.546605\n",
       "2017-08-16   16.914527\n",
       "2017-08-17   16.326046\n",
       "2017-08-18   15.798895\n",
       "\n",
       "[4091 rows x 1 columns]"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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